Senescence at the cellular level reflects changes in gene expression, and is thus amenable to genetic dissection in model organisms. Analysis of senescence one gene at a time has implicated several pathways including central metabolism, free radical accumulation, and insulin function in modulation of longevity, but precluded the development of an integrated understanding of the genome-wide response to aging. The combination of microarray gene expression imaging technology with the power of Drosophila genetics presents a great opportunity for studying how environmental and genetic factors affect rates of senescence through their effects on gene activity. 5000 adult expressed sequence tags will be arrayed on glass slides and hybridized to pairs of messenger RNA preparations labeled with two different fluorescent dyes isolated from flies at various stages of senescence. Comparison of the relative levels of transcript for each of the 5000 genes in up to 150 planned contrasts will allow determination of the frequency, magnitude, and identity of changes in gene expression that accompany functional senescence. The aim of this one year pilot project is to establish a new research tool for research on the genetics of aging, specifically by meeting four objectives: (i) defining the sources and magnitude of the variance in expression levels throughout the genome of the fruitfly, Drosophila melanogaster in replicate treatments; (ii) characterizing the extent of sexual dimorphism in change in gene expression with age; (iii) beginning to study the effects of environmental variables such as temperature and reproductive behavior on gene expression in aging flies; and (iv) conducting a preliminary analysis of the effect of genotypic differences between lines with similar and divergent longevities. The experiments have been designed with the long term objective of integration of microarray studies with quantitative genetic analysis of aging that will allow experimental dissection of the causes of correlated changes in expression of suites of genes in response to different environmental or genetic perturbations. Collaborations will be established with biostatisticians at North Carolina State University to use this model system to develop appropriate protocols for dealing with significance issues in enormous data sets that are being obtained with powerful microarray technology.